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The real-time orbit determination for Low Earth Orbiters (LEOs) is generally based on dual-frequency tracking data from on-board GPS receivers, and positioning accuracies for LEOs currently vary from 0.5 to 1.0 m with sophisticated reduced dynamic orbit determination techniques. In this paper, different strategies are designed and applied to real-time orbit determination only using single-frequency pseudo-range and carrier phase measurements to analyze their corresponding performances. Then some simulative tests are carried out to process the GRACE-A space-borne GPS data in the different solar sunspot activities. The test results demonstrate that the position and velocity accuracy (3DRMS) are up to 0.9 m and 0.9 mm/s respectively using only single-frequency GPS pseudo-range data, and their accuracies could be improved to 0.55 m and 0.55 mm/s using single-frequency combination of pseudo-range and carrier phase measurements, which is close to the dual-frequency real-time orbit determination. Therefore a low-cost single frequency space-borne GPS receiver can be used in real-time orbit determination for LEO missions when appropriate strategies and methods would be selected.

Information systems have been introduced to accumulate real-time tracking data on containers and transporters at container terminals in ports. Logistics managers of container terminals need an intelligent tool to analyze the performance of highly complex and large logistics systems using of the accumulated real-time tracking data. This paper addresses proposing a procedure of analyzing the performance at a real container terminal, especially by making use of the electronic real-time tracking data that is accumulated from united terminal IMSs (IMS: information management system). To analyze the operations performance, all of the operational activities of an actual container terminal in Japan are simulated. It is found that the information obtained by performing simulation is effective for analyzing the performance of the operation.

There is sufficient evidence to show that allowing students to see their own student model is an effective learning and metacognitive strategy. Different tutors have different representations of these open student models, all varying in complexity and detail. EER-Tutor has a number of open student model representations available to the student at any particular time. These include skill meters, kiviat graphs, tag clouds, concept hierarchies, concept lists, and treemaps. Finding out which representation best helps the student at their level of expertise is a difficult task. Do they really understand the representation they are looking at? This paper looks at a novel way of using eye gaze tracking data to see if such data provides us with any clues as to how students use these representations and if they understand them.

We present a novel framework to reliably learn scene entry and exit locations using coherent motion regions formed by weak tracking data. We construct "entities" from weak tracking data at a frame level and then track the entities through time, producing a set of consistent spatio-temporal paths. Resultant entity entry and exit observations of the paths are then clustered and a reliability metric is used to score the behavior of each entry and exit zone. We present experimental results from various scenes and compare against other approaches.

We present a novel multi-camera framework to extract reliable pathlets [1] from tracking data. The proposed approach weights tracks based on their spatial and orientation similarity to simultaneous tracks observed in other camera views. The weighted tracks are used to build a Markovian state space of the environment and Spectral Clustering is employed to extract pathlets from a state-wise similarity matrix. We present experimental results on five multi-camera datasets collected under varying weather conditions and compare with pathlets extracted from individual camera views and three other multi-camera algorithms.

Evaluation of spontaneous infant movements is an important tool for the detection of neurological impairments. It is necessary to automatically detect movement phases which exhibit certain complex characteristics in order to quantitatively assess these movements. This article presents a method to extract segments of complex movements from multivariate kinematic tracking data. Expert knowledge is represented in a principal component model. Evaluation shows a good concordance between the segments marked by the experts and the results of the automated approach. It is further shown that normal infant movements can be discriminated from pathologic movement patterns.

Wireless networks have become so widespread, it is beneficial to determine the ability of cellular networks for localization. This property enables the development of location-based services, providing useful information. These services can be improved by route prediction under the condition of using simple algorithms, because of the limited capabilities of mobile stations. This study gives alternative solutions for this problem of route prediction based on a specific graph model. Our models provide the opportunity to reach our destinations with less effort.

The increasing number of technical devices in modern operating rooms (OR) demands for a modular and flexible integration, interoperability and sharing of resources avoiding multiple redundant technical components within the OR. This paper presents the general concept of a modular tracking infrastructure (MTI) which allows for the separation of an application system and the tracking-device using an Open Surgical Communication Bus.

Risk prevention and alarm are crucial for home care of aged people who live alone. In this paper, an acousticallyanalytic approach is proposed to extract behavioral patterns for modeling and monitoring living activities. An experimental environment was established for collecting sound tracking data of behaviors from daily activities. Each sound tracking data was transcribed to the corresponding sound event sequences by caregivers and psychologists. A living activities mining algorithm is applied to extract meaningful sequences of sound event as behavioral patterns. Then K-means algorithm is adopted to classify events into several fuzzy clusters relating to living activities for modeling behaviors in daily activities. An experimental database consists of 150 sound tracking data was established by collecting three guided behaviors included rolled out of bed to drink water, go to the toilet and watch the fish jar from 5 subjects in two weeks. 476 meaningful sequences of sound events were explored and clustered into 32 quasi-activities. These quasi-activities were further concluded into 5 kinds of behavioral patterns for modeling living activities. The preliminary result shows the potential for modeling and proactively detecting abnormal behaviors or changes of the aged.

Widespread availability of location aware devices (such as GPS receivers) promotes capture of detailed movement trajectories of people, animals, vehicles and other moving objects, opening new options for a better understanding of the processes involved. We investigate spatio-temporal movement patterns in large tracking data sets. Specifically we study so-called 'popular places', that is, regions that are visited by many entities. We present upper and lower bounds.

Technological advances in position aware devices increase the availability of tracking data of everyday objects such as animals, vehicles, people or football players. We propose a geographic data mining approach to detect generic aggregation patterns such as flocking behaviour and convergence in geospatial lifeline data. Our approach considers the object’s motion properties in an analytical space as well as spatial constraints of the object’s lifelines in geographic space. We discuss the geometric properties of the formalised patterns with respect to their efficient computation.

With the rapid advances of wireless and positioning technologies, an interest in LBS (Location-Based Services) is gradually rising. To provide LBS, tracking data should have been stored in database with the proper policies and managed efficiently. In this paper, tracking data management technique using topology is proposed. Tracking data is corresponded to the moving path of an object. In proposed technique, database is updated when moving object arrived at a street intersection or a curved road which is represented as the node in topology and we can predict the location at past and future with attribute of topology and linear function. In this technique, location data that are correspond to the node in topology are stored, thus reduce the number of updates of data. Also as using topology as well as existing location information, accuracy for prediction of location is increased than applying only linear function or spline function.

The paper illustrates how student modeling and advice generation methods can be used to address problems experienced in Web-based distance education courses. We have developed the TADV (Teacher ADVisor) framework which builds student models based on the tracking data collected by a course management system and uses these models to generate advice to the course instructors, so that they can improve their feedback and guidance to distance students. The paper introduces TADV, describes how student, group, and class models are used for generating advice to the teachers, and discusses the viability of this approach based on an evaluative study with users.

It is well known that there are systematic differences between the TOPEX/POSEIDON orbits determined by GPS and by SLR plus DORIS. The residuals of laser tracking data to GPS 35 and GPS 36 also show significant bias. One of the possible reasons of such systematic differences is the uncertainty in the phase center offset of the GPS instrument. The offset of the CHAMP GPS antenna has been measured by the hardware team, and the related numbers are released. But the actual electronic phase center is difficult to be measured accurately. Therefore we try to use the real CHAMP data to estimate the offset again in order to check the validity of the numbers. Our preliminary estimations of the offset have an uncertainty of about 1 cm or less. The results indicate that the official numbers of the offset might need to be corrected by about 1.7 cm in the radial direction.

An integrated GPS monitoring system has been in operation in the about 10-km2 study area at Olkiluoto, Finland since October, 1994. The system includes a permanent GPS station and a local GPS monitoring network. The permanent station is used to investigate regional crustal deformations in Finnish territory, while the local monitoring network is used to monitor relative deformations within the study area. The analysis of 2.8 years of continuous GPS tracking data shows that the horizontal components of the regional crustal deformations are about 2 mm/yr, while the vertical component is about 8 mm/yr. The local GPS monitoring network has been measured six times at half-yearly intervals. The horizontal components of the local movements obtained from the repeated measurements are less than 1.0 mm/yr. The GPS result indicates that the investigation area at Olkiluoto is rather stable.

To take advantage of the quality of the TOPEX/Poseidon sea-level measurements, the radial orbit component must be known to better than a decimeter. Orbits have been produced using Global Positioning System (GPS) and satellite laser ranging (SLR) tracking data. These orbits are produced with small radial position errors (< 5 cm RMS), on a short production schedule (≤ 4 days), with minimal resources. The models and estimation strategies for different data type combinations are outlined. Of special interest are the solutions which contain GPS Anti-Spoofing (AS) data. These orbits are compared to existing precision orbit ephemerides to demonstrate their relative accuracy as an orbit product.

For the studies of the geodynamics, International GPS Service for Geodynamics (IGS) has been producing the precise ephemerides since 1992. However the distribution of the IGS primary fiducial sites is very sparse in and around the Eastern Asia, it is afraid that the precision of the ephemeris is degraded over this area than the North American and Western European area. As a matter of fact, the repeatability of the observations of the Japanese GPS fixed-point network remains 1–2 cm level for the period of 1993 and 1994 (Shimada, 1994). In the paper we examine the Japanese local tracking data incorporated with the IGS global network solutions and the possibility of the improvement of the repeatability by the longer arc approach.

The topic of this paper is to give a survey of the methods used in Space Geodesy (non-geometrical geodesy) with 3 stations located around the Mediterranean Sea when accurate tracking data such as Laser or Doppler measurements are available.

First results of the reduction by the method proposed by Prof. Zhongolovich [1] of simultaneous visual tracking data for satellite 1960 e-3 (the cabin of Soviet Space Ship I) are given in this paper.

The time at which a satellite crosses the plane of the parallel, on which a tracking station is situated, coincides with the time of its crossing the topocentric celestial equator. This can be used for the evaluation of the nodal period of satellites for which $$(1+\frac{H}{R})\sin i>\sin \varphi .$$ In this case tracking data from only one station are needed. This method is considered.